In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01

Our study employed molecular dynamics (MD) simulations to assess the binding affinity between short peptides derived from the tumor-associated antigen glypican 3 (GPC3) and the major histocompatibility complex (MHC) molecule HLA-A*11:01 in hepatocellular carcinoma. We aimed to improve the reliability of <i>in silico</i> predictions of peptide-MHC interactions, which are crucial for developing targeted cancer therapies. We used five algorithms to discover four peptides (TTDHLKFSK, VINTTDHLK, KLIMTQVSK, and STIHDSIQY), demonstrating the substantial potential for HLA-A11:01 presentation. The Anchored Peptide-MHC Ensemble Generator (APE-Gen) was used to create the initial structure of the peptide-MHC complex. This was followed by a 200 ns molecular dynamics (MD) simulation using AMBER22, which verified the precise positioning of the peptides in the binding groove of HLA-A*11:01, specifically at the A and F pockets. Notably, the 2nd residue, which serves as a critical anchor within the 2nd pocket, played a pivotal role in stabilising the binding interactions.VINTTDHLK (Δ<i>G</i> <sub>SIE</sub> = -14.46 ± 0.53 kcal/mol and Δ<i>G</i> <sub>MM/GBSA</sub> = -30.79 ± 0.49 kcal/mol) and STIHDSIQY (Δ<i>G</i> <sub>SIE</sub> and Δ<i>G</i> <sub>MM/GBSA</sub> = -14.55 ± 0.16 and -23.21 ± 2.23 kcal/mol) exhibited the most effective binding potential among the examined peptides, as indicated by both their binding free energies and its binding affinity on the T2 cell line (VINTTDHLK: IC<sub>50</sub> = 0.45 nM; STIHDSIQY: IC<sub>50</sub> = 0.35 nM). The remarkable concordance between <i>in silico</i> and <i>in vitro</i> binding affinity results was of particular significance, indicating that MD simulation is a potent instrument capable of bolstering confidence in <i>in silico</i> peptide predictions. By employing MD simulation as a method, our study provides a promising avenue for improving the prediction of potential peptide-MHC interactions, thereby facilitating the development of more effective and targeted cancer therapies.

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Journal
Heliyon
Published
2024-08-23
DOI
https://doi.org/10.1016/j.heliyon.2024.e36654
Citations
3
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.70

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article

In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01

Kamonpan Sanachai, Nitchakan Darai, Pa‐thai Yenchitsomanus, Wannasiri Chiraphapphaiboon et al.
3 citations
Heliyon
vaccines and immunoinformatics approaches
0.70
article

In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01

Kamonpan Sanachai, Nitchakan Darai, Pa‐thai Yenchitsomanus, Wannasiri Chiraphapphaiboon, Thaweesak Chieochansin, Kornkan Choomee, Chanitra Thuwajit, Thanyada Rungrotmongkol
article en
3 citations

Abstract

Our study employed molecular dynamics (MD) simulations to assess the binding affinity between short peptides derived from the tumor-associated antigen glypican 3 (GPC3) and the major histocompatibility complex (MHC) molecule HLA-A*11:01 in hepatocellular carcinoma. We aimed to improve the reliability of <i>in silico</i> predictions of peptide-MHC interactions, which are crucial for developing targeted cancer therapies. We used five algorithms to discover four peptides (TTDHLKFSK, VINTTDHLK, KLIMTQVSK, and STIHDSIQY), demonstrating the substantial potential for HLA-A11:01 presentation. The Anchored Peptide-MHC Ensemble Generator (APE-Gen) was used to create the initial structure of the peptide-MHC complex. This was followed by a 200 ns molecular dynamics (MD) simulation using AMBER22, which verified the precise positioning of the peptides in the binding groove of HLA-A*11:01, specifically at the A and F pockets. Notably, the 2nd residue, which serves as a critical anchor within the 2nd pocket, played a pivotal role in stabilising the binding interactions.VINTTDHLK (Δ<i>G</i> <sub>SIE</sub> = -14.46 ± 0.53 kcal/mol and Δ<i>G</i> <sub>MM/GBSA</sub> = -30.79 ± 0.49 kcal/mol) and STIHDSIQY (Δ<i>G</i> <sub>SIE</sub> and Δ<i>G</i> <sub>MM/GBSA</sub> = -14.55 ± 0.16 and -23.21 ± 2.23 kcal/mol) exhibited the most effective binding potential among the examined peptides, as indicated by both their binding free energies and its binding affinity on the T2 cell line (VINTTDHLK: IC<sub>50</sub> = 0.45 nM; STIHDSIQY: IC<sub>50</sub> = 0.35 nM). The remarkable concordance between <i>in silico</i> and <i>in vitro</i> binding affinity results was of particular significance, indicating that MD simulation is a potent instrument capable of bolstering confidence in <i>in silico</i> peptide predictions. By employing MD simulation as a method, our study provides a promising avenue for improving the prediction of potential peptide-MHC interactions, thereby facilitating the development of more effective and targeted cancer therapies.

HeliyonVol. 10(17)
Siriraj Hospital (TH), Chulalongkorn University (TH), Khon Kaen University (TH), Mahidol University (TH), Walailak University (TH)
Chulalongkorn University, Karolinska Institutet, Mahidol University, National Science and Technology Development Agency, Faculty of Medicine Siriraj Hospital, Mahidol University
Openalex Percentile: Top 30%
vaccines and immunoinformatics approaches
0.70
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